While the On2 Technologies part of the acquisition by Google may be a significant aspect of the purchase, the technology that Hantro will bring shouldn’t be overlooked. According to an On2 press release at the time of the Hantro acquisition:

Hantro’s technology has been implemented on more than 200 million devices to date and in mobile phones produced by 5 of the top 6 handset manufacturers. Hantro is recognized as the market leader in wireless video intellectual property as measured in revenue, number of shipped devices, and number of customers.

At the time of the Hantro purchase, Eric Ameres, On2’s chief technology officer, was quoted:

This technology allows us to go to the consumer electronics companies, embedded devices, and the handset guys. Embedded technology stretches the battery life, and chipset costs will come down.

The goal is for users on cell phones to experience the same videos that they can on the Web. With this type of technology we’re embedding the ability to get all the same content… and it would look as good as on your PC.

It will be interesting to see how Google moves forward with the technology and business that they are acquiring.

I’ve looked through the US Patent Office databases, and found a number of granted patents and patent applications assigned to On2 Technologies and Hantro Products Oy.

An improved video compression system in which the coefficient transform is sped up via folding transposition of coefficients into the token extraction phase.

This is accomplished by filling a group of blocks coefficient buffers with 0’s before the start of coefficient decoding, extracting the token from the bitstream and placing any extracted coefficient value which is non zero into the transposed order that best suits the target processor.

A method of image and video compression including data re-ordering to improve the performance of the core compression algorithm. In the inventive method, pixel values of at least part of an image are examined and then re-ordered into a new order that has greater compactability than the original pixel order.

The re-ordered pixel values are then compressed, e.g., by block transform. In the particular case of a compression scheme employing a block transform, the inventive method reduces the complexity of the transform coefficients, resulting in more efficient compression.

The method may be added to existing compression algorithms with only minor modifications to the bitstream and decoder architecture.

A method of compressing video data having at least one frame having at least one block and each block having an array of pixels is provided.

The method transforms the pixels of each block into coefficients and creates an optimal transmission order of the coefficients. The method also optimizes the speed of processing compressed video data by partitioning the data bitstream and coding each partition independently.

The method also predicts fractional pixel motion by selecting an interpolation method for each given plurality or block of pixels depending upon at least one metric related to each given block and varies the method from block to block.

The method also enhances error recovery for a current frame using a frame prior to the frame immediately before the current frame as the only reference frame for lessening quality loss during data transmission. Enhanced motion vector coding is also provided.

A method for analysing differences in the content of successive frames of a digital video sequence to create a profile that predicts the likely perceptual significance of and allows separation and classification of different type of signal component.

This invention uses a novel synthesis of several different compression methods, some original and some known in the art, to achieve compression of digitized video image sequences.

Images are color-reduced by a factor of two in both directions using a colorspace that requires minimal computation for reconstruction of RGB pixel values. Images are then transformed into a `token sequence` corresponding to a series of 4.times.4 blocks, using one of seven transformation methods, some dependent on previous frames and some dependent only on pixel values in neighboring blocks.

The resulting token sequence is then compressed using known lossless methods, including Huffman coding.

An apparatus and method for image display and transmission, including display and transmission of data over the Internet. Image transmission is effected by non-sequential streaming of sequential images or of multiple views of a scene or object.

The present invention sends image frames from server to browser out of order. Wherever the cursor is positioned, the browser displays the nearest frame which is received from the server. The viewer, therefore, is able to see more sides of the image without waiting for the entire image to be transmitted.

A method of compressing video data having at least one frame having at least one block and each block having an array of pixels is provided. The method transforms the pixels of each block into coefficients and creates an optimal transmission order of the coefficients. The method also optimizes the speed of processing compressed video data by partitioning the data bitstream and coding each partition independently.

The method also predicts fractional pixel motion by selecting an interpolation method for each given plurality or block of pixels depending upon at least one metric related to each given block and varies the method from block to block.

The method also enhances error recovery for a current frame using a frame prior to the frame immediately before the current frame as the only reference frame for lessening quality loss during data transmission. Enhanced motion vector coding is also provided.

The present invention is a system for serving and playing back a video stream spliced from a plurality of disparate video segments. The system has a video splicing server on the server side and a client application for playback on the client’s side.

The client application is a plug-in that enables the user’s browser program, preferably Netscape and Internet Explorer, to play any known streaming media format.

In order to view the streaming presentation, viewer will connect to a presentation server using the provided client software.

The splicing server, which is used to create a seamless presentation, dynamically splices together disparate segments of the video presentation and feeds the client’s side a sequence of pointers to these video segments, which are played by the provided client software in the order presented, resulting in a coherent show.

Apparatuses, a computer program product and a method for controlling a bit rate of a digital image encoder.

The bit rate controller includes a target cumulative distribution function computing mechanism predicting the number of encoded bits resulting from an encoding to be performed in the encoder;

a counter mechanism counting the number of encoded bits resulting from the encoding;

a check mechanism forming an error term from a comparison between a value of the counter and

a corresponding value of the target cumulative distribution function; and a bit rate control mechanism adjusting a quantization parameter of the encoding to be continued on the basis of the error term.

a processing unit coupled with the input interface to form a frequency domain substitute block from the edge pixels of the pixel domain target block and the edge pixels of the pixel domain blocks adjacent to the pixel domain target block and to form a pixel domain substitute block from the frequency domain substitute block; and

an output interface coupled with the processing unit to place the pixel domain substitute block in position of the pixel domain target block.

In the method, a first digital image and a second digital image are obtained, and a global motion vector is defined between the first digital image and the second digital image.

Next, a mosaic image is combined from the first digital image and the second digital image utilizing the relative locations of the first and second digital images with each other as expressed by the global motion vector.

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Hello Bill – “curiousier and curiousier” as Alice said many times in Wonderland. Most of this technology seems centered around video compression and streaming. This would benefit Google’s vision of universal search and streaming video through search results or creating the ability to increase streaming capacity on You Tube here and overseas where there is still a lot of dialup in action. I’m also intrigued by the content possibilities with regard to relevance of video search results. The patent on analyzing the content of the video sounds like it could be extended beyond the signal content to the actual textual content, i.e. what is spoken, without using the standard spoken to text translation tools.

Let it be known that at the present offer of a fixed 60c worth of GOOG stock, GOOG will in effect make YouTube profitable for .064 what it paid for Youtube, mostly at the expense of the On2 shareholders.

Sounds like a good deal? It is if you’re anyone but an On2 shareholder. Shareholders who have been jerked around and ignored for years by by On2 mangement. Shareholders who have held on despite a concerted effort by naked short selling with FTDs over the last 2 yrs.

The only way out is for GOOG or a competitor to make a reasonable offer. One that the shareholders can’t refuse. If not, there is no option but to sue the daylights out of On2 management for screwing their own shareholders, which the record will confirm. Multiple lawsuits against the players: On2, GOOG and Oxide, have already been lodged.

Thank you for the information about the financial and political issues and problems behind the potential acquisition. I’m personally not a shareholder in any of the companies involved, but I think it’s important to keep in mind the impact that acquisitions can have on people who are. I hope that this does work out well for the people who invested in the company.

As an On2 investor since June ’05, I echo Watermark’s remarks and add that I don’t think that everyone should presume that just because they MIGHT open source an On2 codec, that they should also presume that they will do so with VP8. VP8 never saw the light of day in the marketplace. Google tried it (under NDA) and it is trying to scoop it up at a ridiculously low price. See On2’s August 08 blog for their assessment of what it can do for bandwidth.

Thank you. I’ve seen a lot of people writing about the acquisition, and speculating why, including the possibility of releasing an On2 codec as open source. I’m not making any predictions along those lines at this point.